1. Field of the Invention
The present invention relates generally to the field of image registration and more specifically to the field of image registration configured for medical applications.
2. Related Art
Deformable image registration is a technique for modifying a deformable image in an elastic way to match similar features in a reference image. The technique, in general, involves determining a transform necessary to register (e.g., to align) two images by matching structures of interest in the deformable image and the reference image and to deform the deformable image to achieve alignment of these structures. The deformable and reference images may be images of a patient at different times. The deformable image may be an image of a healthy person and the reference image may be an image of a patient, or vice versa.
For example, the deformable image may include an image of a patient in which a physician has carefully delineated a treatment volume, and the reference image may include an image of the same patient recorded at a later time during treatment. A treatment volume is a spatial volume within a patient to be treated using radiation such as X-rays or particle beams. By deforming the carefully delineated image to align with an image recorded during treatment, movement in the treatment volume can be readily identified. The unaltered reference image, having a treatment volume identified through the image registration process, can then be used to target the new position of the treatment volume during treatment.
The technique has various medical applications. One medical application includes identification of movement or change in organs in medical images acquired at different points in time, for example, changes in patient anatomy since an image was taken at the outset of a treatment plan. Movement or changes in organs can occur due to the spread of cancer, bladder fullness, swelling, breathing, etc.
Another medical application of the deformable image registration technique is segmentation of images using a pre-segmented atlas against which the images are registered. After registration is complete, an identity and/or scope of an anatomical structure within the reference image can be established automatically using previous identification of a corresponding structure within the deformable image. Both medical applications allow for the identification of, for example, changes in an organ during the course of treatment such that the treatment may be altered or discontinued.
Typically, the deformable image registration technique involves determination of a mapping between the two images. This mapping may be bi-directional, e.g., it may be used to map from one image to the other in either direction. As such, the labeling of the two images as the “deformable” image and the “reference” image is typically a convention used for convenience.
The mapping between the two images can be represented by a deformation field (e.g., transformation). For example, the deformation field may be represented by a set of transform vectors representative of the dislocation of pixels between images. Determination of the deformation field includes use of a deformation algorithm that is iteratively applied in two phases. A first phase includes execution of an image based similarity force that alters the deformation field such that the image intensities within the two images match more closely on a pixel by pixel basis. In another phase, a flexibility model is applied to the deformation field. This flexibility model may include determining an internal force field, represented by a set of vectors, that are opposed to the image similarity force.
Various deformation algorithms exist in the prior art, for example, the demons algorithm. The flexibility model in the demons algorithm comprises Gaussian smoothing of the field of displacement vectors. A “similarity” force, opposed to the effect of smoothing displacement vectors, is then applied by using a normalized optical flow. One advantage of the demons algorithm is the speed at which the steps of the algorithm are performed (e.g., on the order of minutes).
A disadvantage of existing deformation algorithms is that all regions of an image are treated equally in each phase. As such, in the registration of an image including both a first organ and a second organ of relatively great interest, those parts of the image including each organ are equally weighted. This may be a disadvantage if the primary purpose of the registration process is to match the second organ.
There is, therefore, a need for improved systems and methods of registering medical images.